Study on the RBF landslide prediction model based on the Grey-Markov theory of time series

Abstract

The accurate prediction of landslide displacement is an important part of social stability and plays an important role in economic development. Therefore, it is a very important topic for how to accurately predict the changes in landslide displacement. According to the research of previous scholars, this paper proposes a multi-model analysis and prediction method that combines gray system preprocessing, radial basis function neural network model, and Markov chain state matrix to predict and modify landslide displacement. Compared with the single RBF model, RMSE and MAPE can be increased to 449.8mm and 0.38%. Grey-PSO-RBF model RMSE and MAPE respectively 437.5mm and 0.33%.No difference between Grey-Markov-RBF and Grey-PSO-RBF.